To use incense we first have to instantiate an experiment loader that will enable us to query the database for specific runs.
| targets_type | iteration | autoencoder_type | batch_size | artifacts | |
|---|---|---|---|---|---|
| exp_id | |||||
| 34 | Mnist | False | Over_dim_tied | 256 | {'history_autoencoder': Artifact(name=history_... |
| 35 | Mnist | False | Over_dim_tied | 128 | {'history_autoencoder': Artifact(name=history_... |
| 36 | Mnist | False | Over_dim_tied | 64 | {'history_autoencoder': Artifact(name=history_... |
| 37 | Mnist | False | Over_dim_tied | 32 | {'history_autoencoder': Artifact(name=history_... |
| 38 | 10_Targets | False | Over_dim_tied | 256 | {'history_autoencoder': Artifact(name=history_... |
| 39 | 10_Targets | False | Over_dim_tied | 128 | {'history_autoencoder': Artifact(name=history_... |
| 40 | 10_Targets | False | Over_dim_tied | 64 | {'history_autoencoder': Artifact(name=history_... |
| 41 | 10_Targets | False | Over_dim_tied | 32 | {'history_autoencoder': Artifact(name=history_... |
| targets_type | iteration | autoencoder_type | batch_size | artifacts | sort | |
|---|---|---|---|---|---|---|
| exp_id | ||||||
| 38 | 10_Targets | False | Over_dim_tied | 256 | {'history_autoencoder': Artifact(name=history_... | 0 |
| 39 | 10_Targets | False | Over_dim_tied | 128 | {'history_autoencoder': Artifact(name=history_... | 1 |
| 40 | 10_Targets | False | Over_dim_tied | 64 | {'history_autoencoder': Artifact(name=history_... | 2 |
| 41 | 10_Targets | False | Over_dim_tied | 32 | {'history_autoencoder': Artifact(name=history_... | 3 |
| 34 | Mnist | False | Over_dim_tied | 256 | {'history_autoencoder': Artifact(name=history_... | 4 |
| 35 | Mnist | False | Over_dim_tied | 128 | {'history_autoencoder': Artifact(name=history_... | 5 |
| 36 | Mnist | False | Over_dim_tied | 64 | {'history_autoencoder': Artifact(name=history_... | 6 |
| 37 | Mnist | False | Over_dim_tied | 32 | {'history_autoencoder': Artifact(name=history_... | 7 |
Red best overall, and also best of subset. Bes means for accuracy max, rest min. Green best of subset.
predictions_df_0
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.9838 | 0.981 | 0.966 | 0.9742 | 0.9777 | 0.9777 | 0.9784 | 0.9798 |
| 1 | 0.9823 | 0.9764 | 0.939 | 0.9689 | 0.9764 | 0.9742 | 0.9782 | 0.9782 |
| 2 | 0.9821 | 0.9759 | 0.8388 | 0.9691 | 0.9738 | 0.9719 | 0.9747 | 0.9698 |
| 3 | 0.9821 | 0.9758 | 0.8187 | 0.9689 | 0.9691 | 0.9649 | 0.9691 | 0.9546 |
| 4 | 0.9821 | 0.9758 | 0.7619 | 0.9689 | 0.9628 | 0.9585 | 0.962 | 0.9336 |
| 5 | 0.9821 | 0.9758 | 0.7616 | 0.9689 | 0.9544 | 0.9484 | 0.9515 | 0.9058 |
| 6 | 0.9821 | 0.9758 | 0.7615 | 0.9689 | 0.9416 | 0.9347 | 0.9371 | 0.8746 |
| 7 | 0.9821 | 0.9758 | 0.7614 | 0.9689 | 0.9274 | 0.9199 | 0.9211 | 0.841 |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.402843 | 0.406489 | 0.395777 | 0.400077 | 0.0142273 | 0.0135879 | 0.0154778 | 0.0284019 |
| 1 | 0.407147 | 0.800692 | 0.408306 | 0.406918 | 0.0220556 | 0.0219748 | 0.0252352 | 0.0442787 |
| 2 | 0.407382 | 2.44856e+10 | 0.427664 | 0.407827 | 0.0327176 | 12804.8 | 0.0380625 | 0.0643806 |
| 3 | 0.4074 | 1.6029e+21 | 0.430916 | 0.407958 | 0.0459869 | 12805 | 19018.1 | 0.0870223 |
| 4 | 0.407401 | inf | 0.442703 | 0.407966 | 164.111 | 12805 | 1.53874e+19 | 0.112242 |
| 5 | 0.407401 | inf | 0.446805 | 0.407966 | 3161.82 | 25606.4 | inf | 1.19025e+12 |
| 6 | 0.407401 | inf | 0.448094 | 0.407967 | 6155.18 | 114887 | inf | 4.31161e+27 |
| 7 | 0.407401 | inf | 0.448288 | 0.407967 | 15973.5 | 202682 | inf | inf |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.26689 | 0.270193 | 0.273218 | 0.268186 | 0.0414262 | 0.0394306 | 0.0430273 | 0.0627057 |
| 1 | 0.267821 | 0.276881 | 0.278261 | 0.269768 | 0.0505998 | 0.0492101 | 0.0539312 | 0.0779905 |
| 2 | 0.267859 | 1364.28 | 0.286771 | 0.269981 | 0.0606934 | 1.13672 | 0.0655467 | 0.0939986 |
| 3 | 0.267863 | 3.48994e+08 | 0.289726 | 0.270016 | 0.0711264 | 1.14721 | 1.40036 | 0.109801 |
| 4 | 0.267863 | 8.92929e+13 | 0.294124 | 0.270018 | 0.202172 | 1.15747 | 3.76367e+07 | 0.125302 |
| 5 | 0.267863 | 2.28463e+19 | 0.295313 | 0.270018 | 2.11776 | 2.24865 | 1.07062e+15 | 9855.67 |
| 6 | 0.267863 | 5.84539e+24 | 0.295689 | 0.270018 | 4.12205 | 10.1626 | 3.04553e+22 | 5.93163e+11 |
| 7 | 0.267863 | 1.49559e+30 | 0.295747 | 0.270018 | 10.5071 | 17.2467 | 8.66343e+29 | 3.57005e+19 |
predictions_df_10
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.9783 | 0.9749 | 0.9585 | 0.9671 | 0.9527 | 0.9529 | 0.9514 | 0.9637 |
| 1 | 0.9744 | 0.9693 | 0.9306 | 0.961 | 0.9626 | 0.9598 | 0.9633 | 0.9674 |
| 2 | 0.9742 | 0.9685 | 0.8275 | 0.9602 | 0.9604 | 0.9561 | 0.9615 | 0.9584 |
| 3 | 0.9741 | 0.9685 | 0.8081 | 0.96 | 0.9554 | 0.9489 | 0.9571 | 0.9379 |
| 4 | 0.9741 | 0.9685 | 0.756 | 0.96 | 0.9472 | 0.9372 | 0.946 | 0.9139 |
| 5 | 0.9741 | 0.9685 | 0.7559 | 0.96 | 0.9362 | 0.9239 | 0.9296 | 0.8838 |
| 6 | 0.9741 | 0.9685 | 0.7557 | 0.96 | 0.9183 | 0.9087 | 0.9121 | 0.8503 |
| 7 | 0.9741 | 0.9685 | 0.7557 | 0.96 | 0.9004 | 0.8903 | 0.89 | 0.8142 |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.402125 | 0.405372 | 0.393313 | 0.398376 | 0.0373236 | 180516 | 626119 | 0.043688 |
| 1 | 0.408081 | 0.413748 | 0.408405 | 0.407693 | 0.042127 | 204880 | 5.06601e+20 | 0.0563758 |
| 2 | 0.408712 | 0.414783 | 0.428755 | 0.409104 | 0.0533446 | 204880 | inf | 0.0752805 |
| 3 | 0.408743 | 0.414965 | 0.432285 | 0.409356 | 422.336 | 204880 | inf | 0.0972759 |
| 4 | 0.408748 | 0.414991 | 0.443466 | 0.409381 | 1687.51 | 217685 | inf | 0.121509 |
| 5 | 0.408748 | 0.414992 | 0.447229 | 0.409387 | 4429.59 | 256100 | nan | 3.38791e+11 |
| 6 | 0.408748 | 0.414992 | 0.448405 | 0.409387 | 10821.5 | 288666 | nan | 1.22725e+27 |
| 7 | 0.408748 | 0.414992 | 0.448596 | 0.409387 | 18500.3 | 382646 | nan | inf |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.267178 | 0.270283 | 0.273126 | 0.268244 | 0.0675787 | 15.6296 | 35.387 | 0.078606 |
| 1 | 0.268489 | 0.272088 | 0.278816 | 0.270371 | 0.0697121 | 17.3004 | 1.00472e+09 | 0.0880597 |
| 2 | 0.268611 | 0.272339 | 0.287446 | 0.270712 | 0.0768396 | 17.3076 | 2.85805e+16 | 0.101744 |
| 3 | 0.268613 | 0.272385 | 0.290337 | 0.27079 | 0.362277 | 17.3163 | 8.13011e+23 | 0.116358 |
| 4 | 0.268614 | 0.272392 | 0.294468 | 0.270797 | 1.17568 | 18.4025 | 2.31272e+31 | 0.1311 |
| 5 | 0.268614 | 0.272392 | 0.295559 | 0.270798 | 2.94163 | 21.6426 | nan | 5262.17 |
| 6 | 0.268614 | 0.272392 | 0.295901 | 0.270798 | 7.11081 | 24.5996 | nan | 3.16698e+11 |
| 7 | 0.268614 | 0.272392 | 0.295957 | 0.270798 | 12.0548 | 32.3657 | nan | 1.9061e+19 |
predictions_df_20
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.9661 | 0.9636 | 0.9461 | 0.9594 | 0.9201 | 0.9149 | 0.9217 | 0.9304 |
| 1 | 0.9557 | 0.9583 | 0.914 | 0.945 | 0.9369 | 0.9295 | 0.9425 | 0.942 |
| 2 | 0.9551 | 0.9579 | 0.8126 | 0.9439 | 0.9346 | 0.9257 | 0.9425 | 0.9328 |
| 3 | 0.9551 | 0.9578 | 0.7909 | 0.9438 | 0.9261 | 0.9156 | 0.9351 | 0.9137 |
| 4 | 0.9551 | 0.9578 | 0.7443 | 0.9436 | 0.9119 | 0.8986 | 0.9222 | 0.8827 |
| 5 | 0.9551 | 0.9578 | 0.7437 | 0.9436 | 0.8959 | 0.8813 | 0.8962 | 0.8488 |
| 6 | 0.9551 | 0.9578 | 0.7437 | 0.9436 | 0.8753 | 0.8604 | 0.8758 | 0.8135 |
| 7 | 0.9551 | 0.9578 | 0.7437 | 0.9436 | 0.8522 | 0.8391 | 0.8511 | 0.7701 |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.40102 | 0.403685 | 0.390298 | 0.397119 | 0.0590926 | 883936 | 3.31396e+06 | 0.0599732 |
| 1 | 0.410223 | 0.415205 | 0.408881 | 0.410071 | 0.0627645 | 1.0116e+06 | 2.68146e+21 | 0.0705858 |
| 2 | 0.411363 | 0.416537 | 0.429943 | 0.412499 | 211.014 | 1.0116e+06 | inf | 0.0895225 |
| 3 | 0.411388 | 0.41663 | 0.434311 | 0.412865 | 1131.21 | 1.02434e+06 | inf | 6.48896e+11 |
| 4 | 0.411388 | 0.416633 | 0.444758 | 0.413032 | 4997.33 | 1.0244e+06 | inf | 2.35058e+27 |
| 5 | 0.411388 | 0.416633 | 0.448318 | 0.413036 | 12822.6 | 1.075e+06 | nan | inf |
| 6 | 0.411388 | 0.416633 | 0.4494 | 0.413036 | 19983.4 | 1.15187e+06 | nan | inf |
| 7 | 0.411388 | 0.416633 | 0.449552 | 0.413036 | 31805.6 | 1.2014e+06 | nan | inf |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.267796 | 0.270376 | 0.273176 | 0.268869 | 0.0868673 | 77.4841 | 126.485 | 0.0935081 |
| 1 | 0.269855 | 0.272937 | 0.279665 | 0.272002 | 0.0863927 | 85.1702 | 3.5957e+09 | 0.0993183 |
| 2 | 0.270111 | 0.273244 | 0.288405 | 0.272628 | 0.227075 | 85.1759 | 1.02285e+17 | 0.111268 |
| 3 | 0.270116 | 0.27326 | 0.291378 | 0.272753 | 0.858623 | 86.2577 | 2.90962e+24 | 7277.04 |
| 4 | 0.270116 | 0.273261 | 0.29518 | 0.272812 | 3.39602 | 86.2688 | 8.2768e+31 | 4.37967e+11 |
| 5 | 0.270116 | 0.273261 | 0.29622 | 0.272813 | 8.38942 | 90.5591 | nan | 2.63598e+19 |
| 6 | 0.270116 | 0.273261 | 0.296538 | 0.272813 | 12.9823 | 97.0312 | nan | 1.58651e+27 |
| 7 | 0.270116 | 0.273261 | 0.296583 | 0.272813 | 20.6104 | 101.723 | nan | inf |
predictions_df_30
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.9459 | 0.9462 | 0.9297 | 0.9427 | 0.8829 | 0.8651 | 0.878 | 0.8838 |
| 1 | 0.9316 | 0.9347 | 0.8946 | 0.9163 | 0.9111 | 0.8875 | 0.9118 | 0.9127 |
| 2 | 0.9298 | 0.933 | 0.7884 | 0.9134 | 0.908 | 0.8798 | 0.9119 | 0.8996 |
| 3 | 0.9297 | 0.9329 | 0.765 | 0.9129 | 0.8948 | 0.8657 | 0.9016 | 0.8721 |
| 4 | 0.9297 | 0.9329 | 0.7283 | 0.9127 | 0.8783 | 0.8454 | 0.8854 | 0.8408 |
| 5 | 0.9297 | 0.9329 | 0.728 | 0.9126 | 0.8573 | 0.823 | 0.8549 | 0.8065 |
| 6 | 0.9297 | 0.9328 | 0.7279 | 0.9126 | 0.8332 | 0.7974 | 0.8295 | 0.7662 |
| 7 | 0.9297 | 0.9328 | 0.7279 | 0.9126 | 0.8056 | 0.7744 | 0.8026 | 0.7276 |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.401364 | 0.403679 | 0.387011 | 0.395785 | 0.0812379 | 1.70153e+06 | 6.24131e+06 | 0.0780647 |
| 1 | 0.415957 | 1.63254e+07 | 0.410203 | 0.415065 | 0.0867466 | 1.81831e+06 | 5.05017e+21 | 4.86324e+07 |
| 2 | 0.417589 | 1.06871e+18 | 0.433102 | 0.419083 | 843.909 | 1.81831e+06 | inf | 1.76167e+23 |
| 3 | 0.417732 | 6.99609e+28 | 0.438297 | 0.419722 | 4594.69 | 1.83112e+06 | inf | inf |
| 4 | 0.417732 | inf | 0.44764 | 0.41987 | 11155.7 | 1.86742e+06 | inf | inf |
| 5 | 0.417732 | inf | 0.450753 | 0.419932 | 17289.7 | 1.93401e+06 | nan | inf |
| 6 | 0.417732 | inf | 0.451669 | 0.419934 | 24303.5 | 2.05957e+06 | nan | nan |
| 7 | 0.417732 | inf | 0.451814 | 0.419934 | 35736.4 | 2.22487e+06 | nan | nan |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.269936 | 0.271745 | 0.273785 | 0.270188 | 0.103917 | 145.311 | 189.433 | 0.108527 |
| 1 | 0.273229 | 35.4951 | 0.281374 | 0.275274 | 0.102642 | 153.039 | 5.38588e+09 | 80.9836 |
| 2 | 0.273623 | 9.01144e+06 | 0.290365 | 0.276372 | 0.649036 | 153.044 | 1.53208e+17 | 4.86721e+09 |
| 3 | 0.273652 | 2.30565e+12 | 0.293345 | 0.276571 | 3.07437 | 154.128 | 4.35822e+24 | 2.92941e+17 |
| 4 | 0.273652 | 5.89917e+17 | 0.296698 | 0.276628 | 7.34871 | 157.274 | 1.23975e+32 | 1.76312e+25 |
| 5 | 0.273652 | 1.50935e+23 | 0.297607 | 0.276648 | 11.2381 | 162.963 | nan | inf |
| 6 | 0.273652 | 3.86178e+28 | 0.297878 | 0.276649 | 15.828 | 173.899 | nan | nan |
| 7 | 0.273652 | inf | 0.297921 | 0.276649 | 23.1719 | 187.924 | nan | nan |
predictions_df_40
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.9088 | 0.9152 | 0.9 | 0.9155 | 0.8287 | 0.8105 | 0.8194 | 0.8279 |
| 1 | 0.8869 | 0.8971 | 0.8595 | 0.8825 | 0.8578 | 0.8349 | 0.8613 | 0.8565 |
| 2 | 0.8847 | 0.8952 | 0.7574 | 0.8798 | 0.8558 | 0.8264 | 0.8609 | 0.8463 |
| 3 | 0.8844 | 0.8949 | 0.738 | 0.8792 | 0.8407 | 0.812 | 0.849 | 0.814 |
| 4 | 0.8844 | 0.8949 | 0.7051 | 0.879 | 0.8166 | 0.7912 | 0.8305 | 0.7814 |
| 5 | 0.8844 | 0.8949 | 0.7049 | 0.879 | 0.7911 | 0.7676 | 0.7998 | 0.7402 |
| 6 | 0.8844 | 0.8949 | 0.7046 | 0.879 | 0.7658 | 0.7422 | 0.7728 | 0.7004 |
| 7 | 0.8844 | 0.8949 | 0.7046 | 0.879 | 0.7377 | 0.7218 | 0.7449 | 0.6663 |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.40483 | 0.402739 | 0.383918 | 0.396252 | 0.103948 | 2.52575e+06 | 7.13224e+06 | 0.0977971 |
| 1 | 0.425784 | 0.425326 | 0.414778 | 0.421516 | 425.388 | 2.79519e+06 | 5.77105e+21 | 0.106349 |
| 2 | 0.427908 | 40.7737 | 0.439398 | 0.426382 | 3164.44 | 2.80429e+06 | inf | 1.78619e+07 |
| 3 | 0.428039 | 2.63022e+12 | 0.445072 | 0.42703 | 9309.65 | 2.84269e+06 | inf | 6.47028e+22 |
| 4 | 0.42804 | 1.72183e+23 | 0.453312 | 0.427173 | 15798.3 | 2.91678e+06 | inf | inf |
| 5 | 0.42804 | inf | 0.455866 | 0.42718 | 23702.4 | 2.95792e+06 | nan | inf |
| 6 | 0.42804 | inf | 0.456654 | 0.42718 | 32169.6 | 3.10959e+06 | nan | inf |
| 7 | 0.42804 | inf | 0.456781 | 0.42718 | 45090.3 | 3.27197e+06 | nan | nan |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.274157 | 0.2737 | 0.275191 | 0.27277 | 0.119765 | 218.981 | 224.646 | 0.123857 |
| 1 | 0.279011 | 0.278898 | 0.284809 | 0.279166 | 0.407303 | 235.488 | 6.38703e+09 | 0.125561 |
| 2 | 0.279475 | 0.334857 | 0.293963 | 0.280419 | 2.15254 | 235.99 | 1.81688e+17 | 38.3152 |
| 3 | 0.2795 | 14137.5 | 0.296832 | 0.280609 | 6.13899 | 239.226 | 5.16834e+24 | 2.29782e+09 |
| 4 | 0.2795 | 3.61709e+09 | 0.299741 | 0.280655 | 10.2659 | 245.573 | 1.4702e+32 | 1.38298e+17 |
| 5 | 0.2795 | 9.2546e+14 | 0.300467 | 0.280657 | 15.3625 | 249.071 | nan | 8.32372e+24 |
| 6 | 0.2795 | 2.36786e+20 | 0.300692 | 0.280657 | 20.8374 | 262.354 | nan | inf |
| 7 | 0.2795 | 6.05835e+25 | 0.300727 | 0.280657 | 29.1036 | 276.142 | nan | nan |
predictions_df_50
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.8586 | 0.8754 | 0.8584 | 0.8791 | 0.7813 | 0.7421 | 0.7715 | 0.7569 |
| 1 | 0.8301 | 0.8483 | 0.8121 | 0.8437 | 0.8109 | 0.7673 | 0.8078 | 0.7876 |
| 2 | 0.8281 | 0.8462 | 0.714 | 0.8386 | 0.8035 | 0.7587 | 0.8115 | 0.7724 |
| 3 | 0.8278 | 0.846 | 0.6961 | 0.8376 | 0.7856 | 0.7406 | 0.7972 | 0.7485 |
| 4 | 0.8278 | 0.846 | 0.6701 | 0.8375 | 0.7588 | 0.7183 | 0.7785 | 0.7082 |
| 5 | 0.8278 | 0.846 | 0.6698 | 0.8375 | 0.7325 | 0.6929 | 0.7458 | 0.6732 |
| 6 | 0.8278 | 0.846 | 0.6697 | 0.8375 | 0.7005 | 0.6692 | 0.7165 | 0.6337 |
| 7 | 0.8278 | 0.846 | 0.6697 | 0.8375 | 0.6745 | 0.6449 | 0.6857 | 0.5984 |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.410291 | 0.403392 | 0.380766 | 0.396454 | 0.12721 | 4.42122e+06 | 2.21598e+07 | 1850.55 |
| 1 | 0.438458 | 0.436516 | 0.419941 | 0.428222 | 211.097 | 4.81468e+06 | 1.7931e+22 | 6.70223e+18 |
| 2 | 0.441038 | 0.441116 | 0.4471 | 0.434723 | 5219.3 | 4.81468e+06 | inf | inf |
| 3 | 0.441256 | 0.441503 | 0.453599 | 0.435611 | 13886.4 | 4.86555e+06 | inf | inf |
| 4 | 0.44128 | 0.441517 | 0.461136 | 0.435791 | 22840.4 | 4.94813e+06 | inf | inf |
| 5 | 0.44128 | 0.441517 | 0.463388 | 0.435797 | 35487.4 | 5.08258e+06 | nan | nan |
| 6 | 0.44128 | 0.441517 | 0.46404 | 0.435797 | 47560.2 | 5.21522e+06 | nan | nan |
| 7 | 0.44128 | 0.441517 | 0.464181 | 0.435797 | 61819.9 | 5.37646e+06 | nan | nan |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.279652 | 0.277233 | 0.277323 | 0.27522 | 0.135244 | 380.437 | 460.318 | 0.527041 |
| 1 | 0.286171 | 0.285365 | 0.289057 | 0.283317 | 0.270596 | 405.093 | 1.30907e+10 | 2.33864e+07 |
| 2 | 0.28676 | 0.286546 | 0.298645 | 0.285066 | 3.52272 | 405.097 | 3.72382e+17 | 1.40755e+15 |
| 3 | 0.28681 | 0.286628 | 0.301496 | 0.285337 | 9.10691 | 409.396 | 1.05929e+25 | 8.4716e+22 |
| 4 | 0.286814 | 0.286628 | 0.304095 | 0.285386 | 14.9043 | 416.579 | 3.01329e+32 | 5.09878e+30 |
| 5 | 0.286814 | 0.286628 | 0.304733 | 0.285387 | 22.9272 | 427.691 | nan | nan |
| 6 | 0.286814 | 0.286628 | 0.304926 | 0.285387 | 30.7271 | 439.112 | nan | nan |
| 7 | 0.286814 | 0.286628 | 0.304971 | 0.285387 | 40.0025 | 452.507 | nan | nan |
predictions_df_60
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.7873 | 0.8113 | 0.7951 | 0.8235 | 0.721 | 0.6804 | 0.7113 | 0.6732 |
| 1 | 0.7557 | 0.7794 | 0.7474 | 0.785 | 0.7473 | 0.702 | 0.7428 | 0.7074 |
| 2 | 0.7525 | 0.7757 | 0.6544 | 0.781 | 0.741 | 0.6928 | 0.7433 | 0.6904 |
| 3 | 0.7521 | 0.7755 | 0.6377 | 0.7804 | 0.7192 | 0.6732 | 0.732 | 0.6618 |
| 4 | 0.7521 | 0.7754 | 0.6169 | 0.7803 | 0.6905 | 0.6494 | 0.7127 | 0.6257 |
| 5 | 0.7521 | 0.7754 | 0.6163 | 0.7802 | 0.6663 | 0.6243 | 0.6778 | 0.5902 |
| 6 | 0.7521 | 0.7754 | 0.6163 | 0.7802 | 0.6406 | 0.5997 | 0.6528 | 0.5511 |
| 7 | 0.7521 | 0.7754 | 0.616 | 0.7802 | 0.6083 | 0.5752 | 0.6244 | 0.5171 |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.417398 | 0.408326 | 0.379036 | 0.399529 | 0.152823 | 5.86798e+06 | 2.44959e+07 | 0.143526 |
| 1 | 0.453891 | 0.451729 | 0.428932 | 0.439389 | 1174.54 | 6.38967e+06 | 1.98213e+22 | 6.82105e+10 |
| 2 | 0.457474 | 0.457266 | 0.458879 | 0.446559 | 10499.5 | 6.4281e+06 | inf | 2.47088e+26 |
| 3 | 0.457815 | 0.457804 | 0.466308 | 0.447465 | 19437.8 | 6.47932e+06 | inf | inf |
| 4 | 0.457817 | 0.457856 | 0.472902 | 0.4476 | 33271.3 | 6.53314e+06 | inf | inf |
| 5 | 0.457817 | 0.457878 | 0.474797 | 0.447651 | 45289.9 | 6.64166e+06 | nan | inf |
| 6 | 0.457817 | 0.457883 | 0.475353 | 0.447651 | 57509 | 6.85152e+06 | nan | nan |
| 7 | 0.457817 | 0.457883 | 0.475509 | 0.447651 | 69673.2 | 7.09927e+06 | nan | nan |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.286747 | 0.283158 | 0.281009 | 0.279812 | 0.150939 | 504.641 | 507.256 | 0.155433 |
| 1 | 0.295163 | 0.293912 | 0.295556 | 0.289611 | 0.933239 | 537.58 | 1.44256e+10 | 2754.45 |
| 2 | 0.295991 | 0.295308 | 0.305509 | 0.291539 | 6.94743 | 540.821 | 4.10354e+17 | 1.65767e+11 |
| 3 | 0.296073 | 0.295427 | 0.308378 | 0.2918 | 12.6422 | 545.13 | 1.16731e+25 | 9.97699e+18 |
| 4 | 0.296073 | 0.295442 | 0.310582 | 0.291845 | 21.6395 | 549.941 | 3.32056e+32 | 6.00483e+26 |
| 5 | 0.296073 | 0.295451 | 0.311118 | 0.291862 | 29.2726 | 559.337 | nan | inf |
| 6 | 0.296073 | 0.295452 | 0.311281 | 0.291862 | 37.1904 | 577.29 | nan | nan |
| 7 | 0.296073 | 0.295452 | 0.311336 | 0.291862 | 44.9696 | 598.505 | nan | nan |
predictions_df_70
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.712 | 0.7241 | 0.7228 | 0.7543 | 0.6585 | 0.6003 | 0.634 | 0.5814 |
| 1 | 0.6755 | 0.6837 | 0.6686 | 0.7148 | 0.6754 | 0.6194 | 0.6654 | 0.6096 |
| 2 | 0.6714 | 0.68 | 0.5845 | 0.71 | 0.6622 | 0.6056 | 0.6668 | 0.5922 |
| 3 | 0.671 | 0.6799 | 0.5691 | 0.7094 | 0.6444 | 0.5839 | 0.6567 | 0.5652 |
| 4 | 0.671 | 0.68 | 0.554 | 0.7093 | 0.6227 | 0.5642 | 0.6363 | 0.5351 |
| 5 | 0.671 | 0.68 | 0.5537 | 0.7093 | 0.5987 | 0.5458 | 0.6048 | 0.5058 |
| 6 | 0.671 | 0.68 | 0.5536 | 0.7093 | 0.5682 | 0.5237 | 0.5809 | 0.4762 |
| 7 | 0.671 | 0.68 | 0.5536 | 0.7093 | 0.5425 | 0.5001 | 0.557 | 0.4506 |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.424893 | 0.416433 | 0.379668 | 0.40174 | 0.179462 | 7.88446e+06 | 4.20404e+07 | 51443.5 |
| 1 | 0.469254 | 0.471375 | 0.441857 | 0.449146 | 1894.19 | 8.42567e+06 | 3.40178e+22 | 1.8635e+20 |
| 2 | 0.473659 | 0.478921 | 0.474173 | 0.458057 | 11057.2 | 8.45348e+06 | inf | inf |
| 3 | 0.474073 | 0.479675 | 0.482592 | 0.459267 | 23399.3 | 8.53513e+06 | inf | inf |
| 4 | 0.474074 | 0.479719 | 0.488431 | 0.459431 | 34722.8 | 8.59214e+06 | inf | inf |
| 5 | 0.474074 | 0.479723 | 0.490332 | 0.459438 | 47389 | 8.70958e+06 | nan | nan |
| 6 | 0.474074 | 0.479722 | 0.490855 | 0.459439 | 62673.1 | 8.87507e+06 | nan | nan |
| 7 | 0.474074 | 0.479722 | 0.49099 | 0.459439 | 75598.8 | 9.00403e+06 | nan | nan |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.293888 | 0.290865 | 0.28649 | 0.284382 | 0.166536 | 675.241 | 766.394 | 2.2191 |
| 1 | 0.30403 | 0.305018 | 0.304186 | 0.295676 | 1.40041 | 708.841 | 2.17967e+10 | 1.2332e+08 |
| 2 | 0.305074 | 0.306905 | 0.314251 | 0.297984 | 7.31724 | 711.446 | 6.20036e+17 | 7.42222e+15 |
| 3 | 0.305172 | 0.307086 | 0.317167 | 0.298324 | 15.3404 | 718.284 | 1.76378e+25 | 4.46719e+23 |
| 4 | 0.305173 | 0.307094 | 0.319062 | 0.29837 | 22.5776 | 722.886 | 5.0173e+32 | 2.68866e+31 |
| 5 | 0.305173 | 0.307092 | 0.319614 | 0.298372 | 30.6874 | 733.065 | nan | nan |
| 6 | 0.305173 | 0.307091 | 0.319766 | 0.298372 | 40.4393 | 746.899 | nan | nan |
| 7 | 0.305173 | 0.307091 | 0.319809 | 0.298372 | 48.7669 | 757.779 | nan | nan |
predictions_df_80
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.6201 | 0.6322 | 0.637 | 0.6695 | 0.5815 | 0.5269 | 0.5545 | 0.4979 |
| 1 | 0.5872 | 0.5943 | 0.5879 | 0.6334 | 0.5949 | 0.5324 | 0.5839 | 0.5232 |
| 2 | 0.583 | 0.5903 | 0.5121 | 0.631 | 0.5837 | 0.5207 | 0.5849 | 0.5108 |
| 3 | 0.5827 | 0.5902 | 0.5008 | 0.6298 | 0.5653 | 0.5084 | 0.5762 | 0.4801 |
| 4 | 0.5827 | 0.5902 | 0.4935 | 0.6298 | 0.54 | 0.4923 | 0.5609 | 0.456 |
| 5 | 0.5827 | 0.5902 | 0.4933 | 0.6297 | 0.5183 | 0.4721 | 0.5341 | 0.4309 |
| 6 | 0.5827 | 0.5902 | 0.493 | 0.6297 | 0.4926 | 0.4559 | 0.5161 | 0.413 |
| 7 | 0.5827 | 0.5902 | 0.493 | 0.6297 | 0.4689 | 0.443 | 0.4974 | 0.3923 |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.436443 | 0.430405 | 0.384682 | 0.406368 | 0.208251 | 9.74844e+06 | 5.6217e+07 | 132070 |
| 1 | 0.486314 | 1.09131e+08 | 0.454558 | 0.462524 | 3732.36 | 1.04488e+07 | 4.54892e+22 | 4.78392e+20 |
| 2 | 0.490589 | 7.14404e+18 | 0.488003 | 0.471316 | 14617.4 | 1.04615e+07 | inf | inf |
| 3 | 0.490844 | 4.67671e+29 | 0.496666 | 0.472457 | 27537.2 | 1.04881e+07 | inf | inf |
| 4 | 0.490855 | inf | 0.501108 | 0.472657 | 39231 | 1.06762e+07 | inf | inf |
| 5 | 0.490855 | inf | 0.502375 | 0.472676 | 50583.6 | 1.08189e+07 | nan | nan |
| 6 | 0.490855 | inf | 0.502751 | 0.472676 | 64751.5 | 1.09616e+07 | nan | nan |
| 7 | 0.490855 | inf | 0.502837 | 0.472676 | 81520.3 | 1.11892e+07 | nan | nan |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.302497 | 0.300678 | 0.293671 | 0.290125 | 0.182696 | 834.933 | 935.025 | 3.90084 |
| 1 | 0.313446 | 91.379 | 0.31238 | 0.303022 | 2.59676 | 879.023 | 2.65933e+10 | 2.23655e+08 |
| 2 | 0.314394 | 2.3299e+07 | 0.322027 | 0.305147 | 9.62583 | 880.099 | 7.56482e+17 | 1.34611e+16 |
| 3 | 0.314446 | 5.96122e+12 | 0.32468 | 0.305444 | 17.8886 | 882.532 | 2.15191e+25 | 8.10179e+23 |
| 4 | 0.314448 | 1.52522e+18 | 0.326063 | 0.305497 | 25.3939 | 898.28 | 6.1214e+32 | 4.8762e+31 |
| 5 | 0.314449 | 3.9024e+23 | 0.326419 | 0.305501 | 32.6098 | 910.452 | nan | nan |
| 6 | 0.314449 | 9.98458e+28 | 0.326535 | 0.305501 | 41.8009 | 922.794 | nan | nan |
| 7 | 0.314449 | inf | 0.326563 | 0.305501 | 52.5019 | 941.838 | nan | nan |
predictions_df_90
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.5258 | 0.5347 | 0.5477 | 0.5696 | 0.4877 | 0.4276 | 0.4648 | 0.4185 |
| 1 | 0.4909 | 0.4943 | 0.5 | 0.5349 | 0.5019 | 0.4427 | 0.494 | 0.4364 |
| 2 | 0.4878 | 0.4904 | 0.4366 | 0.5314 | 0.493 | 0.4332 | 0.4943 | 0.426 |
| 3 | 0.4879 | 0.4901 | 0.4272 | 0.5308 | 0.48 | 0.4205 | 0.4836 | 0.4056 |
| 4 | 0.4879 | 0.4902 | 0.4216 | 0.5307 | 0.4597 | 0.4068 | 0.467 | 0.3886 |
| 5 | 0.4879 | 0.4902 | 0.4212 | 0.5307 | 0.444 | 0.3921 | 0.44 | 0.3664 |
| 6 | 0.4879 | 0.4902 | 0.4212 | 0.5307 | 0.4305 | 0.379 | 0.4254 | 0.3489 |
| 7 | 0.4879 | 0.4902 | 0.4212 | 0.5307 | 0.4108 | 0.3668 | 0.4126 | 0.3301 |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.445065 | 0.437497 | 0.387168 | 0.41089 | 0.240506 | 1.35461e+07 | 6.57491e+07 | 352749 |
| 1 | 0.502291 | 0.51108 | 0.467161 | 0.475999 | 2534.91 | 1.47513e+07 | 5.32023e+22 | 1.27771e+21 |
| 2 | 0.506685 | 0.519687 | 0.50146 | 0.485716 | 15143.6 | 1.47717e+07 | inf | inf |
| 3 | 0.507073 | 0.520529 | 0.511031 | 0.486989 | 29559.8 | 1.4879e+07 | inf | inf |
| 4 | 0.507081 | 0.520673 | 0.515045 | 0.487153 | 42813.9 | 1.49731e+07 | inf | inf |
| 5 | 0.507081 | 0.520686 | 0.516242 | 0.487179 | 56596.2 | 1.51798e+07 | nan | nan |
| 6 | 0.507081 | 0.520686 | 0.516614 | 0.48718 | 69377.1 | 1.53626e+07 | nan | nan |
| 7 | 0.507081 | 0.520686 | 0.516744 | 0.48718 | 83560.9 | 1.55018e+07 | nan | nan |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.310092 | 0.308183 | 0.299873 | 0.295911 | 0.199425 | 1164.99 | 1117.59 | 6.92175 |
| 1 | 0.322415 | 0.326559 | 0.320382 | 0.31062 | 1.84678 | 1240.91 | 3.17863e+10 | 4.04333e+08 |
| 2 | 0.323316 | 0.328659 | 0.329699 | 0.312928 | 9.97175 | 1243 | 9.04203e+17 | 2.43355e+16 |
| 3 | 0.3234 | 0.328872 | 0.332457 | 0.313238 | 19.214 | 1251.68 | 2.57212e+25 | 1.46467e+24 |
| 4 | 0.3234 | 0.328912 | 0.333667 | 0.313284 | 27.7209 | 1260.11 | 7.31675e+32 | inf |
| 5 | 0.3234 | 0.328915 | 0.333999 | 0.313288 | 36.5904 | 1277.21 | nan | nan |
| 6 | 0.3234 | 0.328915 | 0.33411 | 0.313289 | 44.7494 | 1292.49 | nan | nan |
| 7 | 0.3234 | 0.328915 | 0.334153 | 0.313289 | 53.8455 | 1304.25 | nan | nan |
predictions_df_100
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.4324 | 0.4416 | 0.4537 | 0.4836 | 0.4127 | 0.3567 | 0.3812 | 0.3548 |
| 1 | 0.4006 | 0.4066 | 0.4127 | 0.4543 | 0.4223 | 0.3616 | 0.4079 | 0.3614 |
| 2 | 0.3986 | 0.4038 | 0.3644 | 0.452 | 0.4144 | 0.3535 | 0.4062 | 0.3526 |
| 3 | 0.3983 | 0.403 | 0.3585 | 0.4519 | 0.4014 | 0.3467 | 0.3978 | 0.3373 |
| 4 | 0.3982 | 0.403 | 0.3548 | 0.4518 | 0.3811 | 0.3335 | 0.3897 | 0.3232 |
| 5 | 0.3982 | 0.403 | 0.3545 | 0.4518 | 0.3662 | 0.3195 | 0.3625 | 0.3048 |
| 6 | 0.3982 | 0.403 | 0.3542 | 0.4518 | 0.3526 | 0.3121 | 0.3544 | 0.2909 |
| 7 | 0.3982 | 0.403 | 0.3542 | 0.4518 | 0.338 | 0.3016 | 0.3454 | 0.2828 |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.454725 | 0.45108 | 0.39497 | 0.419231 | 0.27189 | 1.89169e+07 | 9.15463e+07 | 7.21208e+06 |
| 1 | 0.518014 | 0.53049 | 0.481865 | 0.489098 | 2953.55 | 2.03214e+07 | 7.40765e+22 | 2.61243e+22 |
| 2 | 0.523514 | 0.539329 | 0.516644 | 0.498944 | 14789.5 | 2.03342e+07 | inf | inf |
| 3 | 0.523904 | 0.54019 | 0.526589 | 0.499971 | 31879 | 2.03836e+07 | inf | inf |
| 4 | 0.523926 | 0.540274 | 0.530323 | 0.500032 | 46811.5 | 2.04392e+07 | inf | inf |
| 5 | 0.523928 | 0.540276 | 0.531252 | 0.500087 | 62903.4 | 2.06526e+07 | nan | nan |
| 6 | 0.523928 | 0.540276 | 0.531524 | 0.500093 | 77770.4 | 2.08556e+07 | nan | nan |
| 7 | 0.523928 | 0.540276 | 0.531578 | 0.500093 | 94271 | 2.10574e+07 | nan | nan |
| Over_dim_tied 256 10_Targets | Over_dim_tied 128 10_Targets | Over_dim_tied 64 10_Targets | Over_dim_tied 32 10_Targets | Over_dim_tied 256 Mnist | Over_dim_tied 128 Mnist | Over_dim_tied 64 Mnist | Over_dim_tied 32 Mnist | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.318187 | 0.317664 | 0.307869 | 0.302561 | 0.21702 | 1620.48 | 1661.19 | 63.6357 |
| 1 | 0.331444 | 0.337099 | 0.329051 | 0.317666 | 2.11387 | 1709.43 | 4.72491e+10 | 3.81653e+09 |
| 2 | 0.332533 | 0.339079 | 0.337847 | 0.319945 | 9.787 | 1710.51 | 1.34406e+18 | 2.29704e+17 |
| 3 | 0.332607 | 0.339285 | 0.340557 | 0.320195 | 20.8379 | 1714.74 | 3.82337e+25 | 1.38252e+25 |
| 4 | 0.332612 | 0.339305 | 0.341615 | 0.32021 | 30.3468 | 1719.8 | 1.08761e+33 | inf |
| 5 | 0.332612 | 0.339305 | 0.341869 | 0.320231 | 40.5508 | 1737.37 | nan | nan |
| 6 | 0.332612 | 0.339305 | 0.341938 | 0.320233 | 50.1415 | 1754.52 | nan | nan |
| 7 | 0.332612 | 0.339305 | 0.341949 | 0.320233 | 60.8013 | 1771.73 | nan | nan |